Artificial neural network approaches on composition–property relationships of jet fuels based on GC–MS

Liquid Fuels and Propellants for Aerospace Propulsion: 1903-2003

Tim Edwards · Journal of Propulsion and Power · 2003 · 608 citations

Liquid Rocket, Chemical Propulsion, Engineering +10

Advanced aviation fuels: a look ahead via a historical perspective

L. Maurice, Herbert R. Lander, T. Edwards et al. · Fuel · 2001 · 232 citations

Aviation Systems, Engineering, Advanced Aviation Fuels +6

Artificial neural networks used for the prediction of the cetane number of biodiesel

Arumugam Sakunthalai Ramadhas, S. Jayaraj, C. Muraleedharan et al. · Renewable Energy · 2006 · 153 citations

Cetane Number, Artificial Neural Networks, Engineering +7

Diesel Fuel Analysis by GC−FIMS:  Aromatics, <i>n</i>-Paraffins, and Isoparaffins

Yevgenia Briker, Zbigniew Ring, A. Iacchelli et al. · Energy & Fuels · 2000 · 113 citations

Diesel Fuel, Chemical Engineering, Engineering +15

Neural network prediction of cetane number and density of diesel fuel from its chemical composition determined by LC and GC–MS

Hong Yang, Zbigniew Ring, Yevgenia Briker et al. · Fuel · 2002 · 104 citations

Diesel Fuel, Engineering, Neural Network Prediction +4